Determination of benzo[a]pyrene in cigarette mainstream smoke by using mid-infrared spectroscopy associated with a novel chemometric algorithm

• MIR spectroscopy was used to analyze benzo[a]pyrene (BaP) in cigarette smoke.
• A novel adaptive parameter-free algorithm named DPSO-WPT-PLS approach was proposed.
• DPSO-WPT-PLS models the MIR of cigarette samples with promising results.
• A simple, fast, and inexpensive analysis of BaP in cigarette smoke is developed.

Determination of benzo[a]pyrene (BaP) in cigarette smoke can be very important for the tobacco quality control and the assessment of its harm to human health. In this study, mid-infrared spectroscopy (MIR) coupled to chemometric algorithm (DPSO-WPT-PLS), which was based on the wavelet packet transform (WPT), discrete particle swarm optimization algorithm (DPSO) and partial least squares regression (PLS), was used to quantify harmful ingredient benzo[a]pyrene in the cigarette mainstream smoke with promising result. Furthermore, the proposed method provided better performance compared to several other chemometric models, i.e., PLS, radial basis function-based PLS (RBF-PLS), PLS with stepwise regression variable selection (Stepwise-PLS) as well as WPT-PLS with informative wavelet coefficients selected by correlation coefficient test (rtest-WPT-PLS). It can be expected that the proposed strategy could become a new effective, rapid quantitative analysis technique in analyzing the harmful ingredient BaP in cigarette mainstream smoke.

Mid-infrared spectroscopy (MIR) coupled to a novel chemometric algorithm, DPSO-WPT-PLS, was used to quantify harmful ingredient benzo[a]pyrene in the cigarette mainstream smoke with promising result.Figure optionsDownload as PowerPoint slide